Industrial
Advancing Industrial Autonomy
Modern manufacturing would come to a standstill without industrial robots. Robotics and many other industrial applications, from monitoring machine metrics to analyzing customer traffic patterns in retail, rely on edge AI to analyze data that matters locally and make decisions in real time.
Edge AI Saves Time and Money
Manufacturers are retooling their processes with AI at the edge to gain improvements in predictive maintenance, quality control, equipment efficiency, and yield optimization. In the past, most data processing occurred in a data center or the cloud. However, sending data to the cloud adds latency and can cause the information to arrive too late to be actionable. With edge AI, machines can make autonomous decisions immediately because the processing occurs locally. Efficient edge computing reduces data transfers, saving time and money. OEMs and chipmakers are adding AI capabilities to their products to capitalize on the advantages of edge processing.
Best AI for Industrial Uses
Future industrial systems will process more extensive neural networks and a growing number of input streams. Edge processing will require highly efficient hardware solutions. Adding the Expedera Origin™ NPUs to your silicon solution can improve performance without increasing costs. Origin NPUs can run trained models without modification, ensuring the most accurate results while saving engineering time often spent reoptimizing models. The architecture can efficiently run multiple Neural Networks (NN) concurrently. Additionally, Expedera offers capabilities for future NN support to ensure a future-proof product.
An Ideal Architecture for Industrial
The Origin E2 neural engine uses Expedera’s unique packet-based architecture, which is far more efficient than common layer-based architectures. The architecture enables parallel execution across multiple layers, achieving better resource utilization and deterministic performance. It also eliminates the need for hardware-specific optimizations, allowing customers to run their trained neural networks unchanged without reducing model accuracy. This innovative approach greatly increases performance while lowering power, area, and latency.
A Solution that Scales Across Applications
Industrial AI requirements range from GOPS to TOPS. Sourcing AI architecture that supports high utilization and efficiencies across that range could be difficult – not with Expedera. Our Origin IP supports from 3 GOPS to 128 TOPS, allowing for a single IP to solve all your needs, today and tomorrow.
Area-Efficient for Cost-Effective Deployments
One of the hardest challenges in deploying AI is finding a solution that fits the tight budgets of OEMs. Expedera’s Origin NPU requires minimal silicon area, ensuring that AI can be deployed in industrial chips cost-effectively.
Optimized for Model Accuracy
Expedera’s field-proven IP and software stack allows you to run your trained standard, custom, and proprietary neural networks as-is. We required no hardware or software optimizations or accuracy sacrifices.
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